Effect of sampling frequency on EMG power spectral characteristics

Area of Science:

• Biomedical Engineering
• Neuroscience
• Signal Processing

Background:

• Surface electromyography (EMG) digitization relies on Analog-to-Digital (A/D) converters, where the sampling rate is a critical parameter.
• An inappropriate sampling rate can introduce noise or lead to signal errors, impacting data integrity.
• Understanding the effect of sampling rate on EMG signal characteristics is vital for accurate analysis.

Purpose of the Study:

• To investigate the impact of varying sampling rates on the power spectrum of surface EMG signals.
• To determine the optimal sampling rate for EMG analysis, balancing signal fidelity and data processing.

Main Methods:

• EMG signals were recorded from the deltoid muscle of nine subjects during maximal voluntary contraction.
• Recordings were performed at sampling rates of 4, 6, 8, and 10 KHz.
• A biopotential coupler with a 5 Hz to 2 KHz response range was used, and signals were processed using Fast Fourier Transform (FFT) software.

Main Results:

• A linear relationship was observed between the sampling rate and the Mean Power Frequency (MPF) of the EMG signal.
• No significant effect of sampling rate was found on the mean amplitude or Root Mean Square (RMS) values of the digitized EMG signal.
• The power spectrum analysis revealed distinct changes in MPF with varying digitization rates.

Conclusions:

• The sampling rate significantly influences the Mean Power Frequency (MPF) in surface EMG signals, indicating its importance for spectral analysis.
• Mean and RMS values of the EMG signal are less sensitive to the chosen sampling rate within the tested range.
• Careful selection of sampling rates is recommended for accurate EMG spectral analysis, particularly when evaluating MPF.